Markov Logic
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| Author | : Pedro Dechter |
| Publisher | : Springer Nature |
| Total Pages | : 145 |
| Release | : 2022-05-31 |
| Genre | : Computers |
| ISBN | : 3031015495 |
Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.g., the Internet in networking, the relational model in databases, etc.). So far this interface layer has been missing in AI. First-order logic and probabilistic graphical models each have some of the necessary features, but a viable interface layer requires combining both. Markov logic is a powerful new language that accomplishes this by attaching weights to first-order formulas and treating them as templates for features of Markov random fields. Most statistical models in wide use are special cases of Markov logic, and first-order logic is its infinite-weight limit. Inference algorithms for Markov logic combine ideas from satisfiability, Markov chain Monte Carlo, belief propagation, and resolution. Learning algorithms make use of conditional likelihood, convex optimization, and inductive logic programming. Markov logic has been successfully applied to problems in information extraction and integration, natural language processing, robot mapping, social networks, computational biology, and others, and is the basis of the open-source Alchemy system. Table of Contents: Introduction / Markov Logic / Inference / Learning / Extensions / Applications / Conclusion
| Author | : European Coordinating Committee for Artificial Intelligence |
| Publisher | : IOS Press |
| Total Pages | : 972 |
| Release | : 2008 |
| Genre | : Computers |
| ISBN | : 1586038915 |
Includes subconference "Prestigious Applications of Intelligent Systems (PAIS 2008)."
| Author | : Pedro Domingos |
| Publisher | : Morgan & Claypool Publishers |
| Total Pages | : 156 |
| Release | : 2009-05-08 |
| Genre | : Computers |
| ISBN | : 1598296949 |
Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.g., the Internet in networking, the relational model in databases, etc.). So far this interface layer has been missing in AI. First-order logic and probabilistic graphical models each have some of the necessary features, but a viable interface layer requires combining both. Markov logic is a powerful new language that accomplishes this by attaching weights to first-order formulas and treating them as templates for features of Markov random fields. Most statistical models in wide use are special cases of Markov logic, and first-order logic is its infinite-weight limit. Inference algorithms for Markov logic combine ideas from satisfiability, Markov chain Monte Carlo, belief propagation, and resolution. Learning algorithms make use of conditional likelihood, convex optimization, and inductive logic programming. Markov logic has been successfully applied to problems in information extraction and integration, natural language processing, robot mapping, social networks, computational biology, and others, and is the basis of the open-source Alchemy system.
| Author | : Luc De Raedt |
| Publisher | : Springer |
| Total Pages | : 348 |
| Release | : 2008-02-26 |
| Genre | : Computers |
| ISBN | : 354078652X |
This book provides an introduction to probabilistic inductive logic programming. It places emphasis on the methods based on logic programming principles and covers formalisms and systems, implementations and applications, as well as theory.
| Author | : Hang Li |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 701 |
| Release | : 2008-05-29 |
| Genre | : Computers |
| ISBN | : 3540686339 |
This book constitutes the thoroughly refereed post-conference proceedings of the 4th Asia Information Retrieval Symposium, AIRS 2008, held in Harbin, China, in May 2008. The 39 revised full papers and 43 revised poster papers presented were carefully reviewed and selected from 144 submissions. All current issues in information retrieval are addressed: applications, systems, technologies and theoretical aspects of information retrieval in text, audio, image, video and multi-media data. The papers are organized in topical sections on IR models image retrieval, text classification, chinese language processing, text processing, application of IR, machine learning, taxonomy, IR methods, information extraction, summarization, multimedia, Web IR, and text clustering.
| Author | : |
| Publisher | : IOS Press |
| Total Pages | : 3525 |
| Release | : |
| Genre | : |
| ISBN | : |
| Author | : Joachim Hertzberg |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 525 |
| Release | : 2007-08-30 |
| Genre | : Computers |
| ISBN | : 3540745645 |
This book constitutes the thoroughly refereed proceedings of the 30th Annual German Conference on Artificial Intelligence, KI 2007, held in Osnabrück, Germany, September 2007. The papers are organized in topical sections on cognition and emotion, semantic Web, analogy, natural language, reasoning, ontologies, spatio-temporal reasoning, machine learning, spatial reasoning, robot learning, classical AI problems, and agents.
| Author | : Hamido Fujita |
| Publisher | : Springer |
| Total Pages | : 1019 |
| Release | : 2016-07-13 |
| Genre | : Computers |
| ISBN | : 3319420070 |
This book constitutes the refereed conference proceedings of the 29th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, held in Morioka, Japan, in August 2-4, 2016. The 80 revised full papers presented were carefully reviewed and selected from 168 submissions. They are organized in topical sections: data science; knowledge base systems; natural language processing and sentiment analysis; semantic Web and social networks; computer vision; medical diagnosis system and bio-informatics; applied neural networks; innovations in intelligent systems and applications; decision support systems; adaptive control; soft computing and multi-agent systems; evolutionary algorithms and heuristic search; system integration for real-life applications.
| Author | : Walter Daelemans |
| Publisher | : Springer |
| Total Pages | : 714 |
| Release | : 2008-08-17 |
| Genre | : Computers |
| ISBN | : 3540874798 |
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
| Author | : P. Hitzler |
| Publisher | : IOS Press |
| Total Pages | : 410 |
| Release | : 2022-01-19 |
| Genre | : Computers |
| ISBN | : 1643682458 |
Neuro-symbolic AI is an emerging subfield of Artificial Intelligence that brings together two hitherto distinct approaches. ”Neuro” refers to the artificial neural networks prominent in machine learning, ”symbolic” refers to algorithmic processing on the level of meaningful symbols, prominent in knowledge representation. In the past, these two fields of AI have been largely separate, with very little crossover, but the so-called “third wave” of AI is now bringing them together. This book, Neuro-Symbolic Artificial Intelligence: The State of the Art, provides an overview of this development in AI. The two approaches differ significantly in terms of their strengths and weaknesses and, from a cognitive-science perspective, there is a question as to how a neural system can perform symbol manipulation, and how the representational differences between these two approaches can be bridged. The book presents 17 overview papers, all by authors who have made significant contributions in the past few years and starting with a historic overview first seen in 2016. With just seven months elapsed from invitation to authors to final copy, the book is as up-to-date as a published overview of this subject can be. Based on the editors’ own desire to understand the current state of the art, this book reflects the breadth and depth of the latest developments in neuro-symbolic AI, and will be of interest to students, researchers, and all those working in the field of Artificial Intelligence.
